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Wei Vivian Li
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2020 – today
- 2023
- [j10]Andrew Cheng, Guanyu Hu, Wei Vivian Li:
Benchmarking cell-type clustering methods for spatially resolved transcriptomics data. Briefings Bioinform. 24(1) (2023) - [j9]Jiayi Liu, Anat Kreimer, Wei Vivian Li:
Differential variability analysis of single-cell gene expression data. Briefings Bioinform. 24(5) (2023) - [j8]Xinwei He, Kun Qian, Ziqian Wang, Shirou Zeng, Hongwei Li, Wei Vivian Li:
scAce: an adaptive embedding and clustering method for single-cell gene expression data. Bioinform. 39(9) (2023) - 2022
- [j7]Tianyi Sun, Dongyuan Song, Wei Vivian Li, Jingyi Jessica Li:
Simulating Single-Cell Gene Expression Count Data with Preserved Gene Correlations by scDesign2. J. Comput. Biol. 29(1): 23-26 (2022) - [j6]Kun Qian, Shiwei Fu, Hongwei Li, Wei Vivian Li:
The scINSIGHT Package for Integrating Single-Cell RNA-Seq Data from Different Biological Conditions. J. Comput. Biol. 29(11): 1233-1236 (2022) - [c1]Kun Qian, Shiwei Fu, Hongwei Li, Wei Vivian Li:
A Novel Matrix Factorization Model for Interpreting Single-Cell Gene Expression from Biologically Heterogeneous Data. RECOMB 2022: 353-355 - 2021
- [j5]Jie Sheng, Wei Vivian Li:
Selecting gene features for unsupervised analysis of single-cell gene expression data. Briefings Bioinform. 22(6) (2021) - [j4]Wei Vivian Li, Yanzeng Li:
scLink: Inferring Sparse Gene Co-expression Networks from Single-cell Expression Data. Genom. Proteom. Bioinform. 19(3): 475-492 (2021) - 2020
- [i1]Wei Vivian Li, Xin Tong, Jingyi Jessica Li:
Bridging Cost-sensitive and Neyman-Pearson Paradigms for Asymmetric Binary Classification. CoRR abs/2012.14951 (2020)
2010 – 2019
- 2019
- [j3]Wei Vivian Li, Jingyi Jessica Li:
A statistical simulator scDesign for rational scRNA-seq experimental design. Bioinform. 35(14): i41-i50 (2019) - 2018
- [j2]Wei Vivian Li, Jingyi Jessica Li:
Modeling and analysis of RNA-seq data: a review from a statistical perspective. Quant. Biol. 6(3): 195-209 (2018) - 2016
- [j1]Wei Vivian Li, Zahra S. Razaee, Jingyi Jessica Li:
Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states. BMC Genom. 17(S-1): 10 (2016)
Coauthor Index
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